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Record W2795000734 · doi:10.1139/cgj-2017-0582

Assessment of engineering behaviour of an intensely weathered swelling mudstone under full range of seasonal variation and the relationships among measured parameters

2018· article· en· W2795000734 on OpenAlexvenueno aff
Zhixiong Zeng, Lingwei Kong, Min Wang, Hossain Md. Sayem

Bibliographic record

VenueCanadian Geotechnical Journal · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsnot available
Fundersnot available
KeywordsCohesion (chemistry)Geotechnical engineeringElectrical resistivity and conductivityWettingShear (geology)Materials sciencePorosityFriction angleInternal frictionMineralogyComposite materialGeologyChemistry

Abstract

fetched live from OpenAlex

An experimental study was conducted to investigate the physical and mechanical properties of an intensely weathered mudstone from Northeast China after wetting–drying (W–D), freezing–thawing (F–T), and wetting–drying–freezing–thawing (W–D–F–T) cycles. These cyclic climatic processes have significant effects on the volume, microstructure, stress–strain behaviour, shear strength, electrical resistivity, and P-wave velocity of the samples. The variation in electrical resistivity exhibits an inverse correlation with the volume change, and a strong relationship can be observed between the electrical resistivity and porosity. The cohesion decreases with increasing number of cycles, while the internal friction angle slightly increases; these relationships can be caused by the presence of cracks and large voids and by the increase in the aggregate size and density during the drying and freezing processes, respectively. Moreover, the W–D–F–T cycles have a greater influence on the shear strength than do either the W–D or F–T cycles. This phenomenon is similar to that observed in the P-wave velocity, and the relationships between the shear strength parameters and P-wave velocity are also explored. This study provides nondestructive methods of predicting the deformation and shear strength of mudstones in seasonally frozen regions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.047
GPT teacher head0.239
Teacher spread0.192 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations55
Published2018
Admission routes1
Has abstractyes

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